Suppressors of cGAS‐STING are downregulated during fin‐limb regeneration and aging in aquatic vertebrates
Bibliographic record
Abstract
During the early stages of limb and fin regeneration in aquatic vertebrates (i.e., fishes and amphibians), blastema undergo transcriptional rewiring of innate immune signaling pathways to promote immune cell recruitment. In mammals, a fundamental component of innate immune signaling is the cytosolic DNA sensing pathway, cGAS-STING. However, to what extent the cGAS-STING pathway influences regeneration in aquatic anamniotes is unknown. In jawed vertebrates, negative regulation of cGAS-STING activity is accomplished by suppressors of cytosolic DNA such as Trex1, Pml, and PML-like exon 9 (Plex9) exonucleases. Here, we examine the expression of these suppressors of cGAS-STING, as well as inflammatory genes and cGAS activity during caudal fin and limb regeneration using the spotted gar (Lepisosteus oculatus) and axolotl (Ambystoma mexicanum) model species, and during age-related senescence in zebrafish (Danio rerio). In the regenerative blastema of wounded gar and axolotl, we observe increased inflammatory gene expression, including interferon genes and interleukins 6 and 8. We also observed a decrease in axolotl Trex1 and gar pml expression during the early phases of wound healing which correlates with a dramatic increase in cGAS activity. In contrast, the plex9.1 gene does not change in expression during wound healing in gar. However, we observed decreased expression of plex9.1 in the senescing cardiac tissue of aged zebrafish, where 2'3'-cGAMP levels are elevated. Finally, we demonstrate a similar pattern of Trex1, pml, and plex9.1 gene regulation across species in response to exogenous 2'3'-cGAMP. Thus, during the early stages of limb-fin regeneration, Pml, Trex1, and Plex9.1 exonucleases are downregulated, presumably to allow an evolutionarily ancient cGAS-STING activity to promote inflammation and the recruitment of immune cells.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".